摘要:
Structural element candidates, estimated to be predetermined structural elements of a predetermined subject, are detected from an image that includes the subject. The subject that includes the structural element candidates is detected from the image in the vicinity of the detected structural element candidates. The characteristics of the structural elements are discriminated from the image in the vicinity of the structural element candidates, at a higher accuracy than when the structural elements were detected. In the case that the characteristics of the structural elements are discriminated, the structural element candidates are confirmed as being the predetermined structural elements.
摘要:
Structural element candidates, estimated to be predetermined structural elements of a predetermined subject, are detected from an image that includes the subject. The subject that includes the structural element candidates is detected from the image in the vicinity of the detected structural element candidates. The characteristics of the structural elements are discriminated from the image in the vicinity of the structural element candidates, at a higher accuracy than when the structural elements were detected. In the case that the characteristics of the structural elements are discriminated, the structural element candidates are confirmed as being the predetermined structural elements.
摘要:
First, a face within an image, which is a target of detection, is detected. Detection data of the face is employed to detect eyes which are included in the face. Detection data of the eyes are employed to detect the inner and outer corners of the eyes. Detection data of the inner and outer corners of the eyes is employed to detect characteristic points of the upper and lower eyelids that represent the outline of the eyes.
摘要:
First, a face within an image, which is a target of detection, is detected. Detection data of the face is employed to detect eyes which are included in the face. Detection data of the eyes are employed to detect the inner and outer corners of the eyes. Detection data of the inner and outer corners of the eyes is employed to detect characteristic points of the upper and lower eyelids that represent the outline of the eyes.
摘要:
A plurality of different facial images is used to cause a face classification apparatus to learn a characteristic feature of a face by using a machine-learning method. Each of the facial images includes a face which has the same direction and the same angle of inclination as those of a face included in each of the other facial images and each of the facial images is limited to an image of a specific facial region. For example, the facial region is a predetermined region including only a specific facial part other than a region below an upper lip to avoid an influence of a change in facial expressions. Alternatively, if the apparatus is used to detect a frontal face and to perform refined detection processing on the extracted face candidate, a region including only an eye or eyes, a nose and an upper lip is used as the facial region.
摘要:
First, a face within an image, which is a target of detection, is detected. Detection data of the face is employed to detect eyes which are included in the face. Detection data of the eyes are employed to detect the inner and outer corners of the eyes. Detection data of the inner and outer corners of the eyes is employed to detect characteristic points of the upper and lower eyelids that represent the outline of the eyes.
摘要:
To detect a face image in an inputted image, predetermined-size partial images are cut out at different positions in the inputted image. An indicator value indicating a probability of each partial image being the face image is calculated. The partial images having the indicator values not less than a first threshold are extracted as candidate face images. Each candidate is set as a candidate of interest. If any nearby candidate is present within a predetermined coordinate distance from the candidate of interest, the candidate of interest and the nearby candidate are set in one candidate group. For each candidate group, an integrated indicator value reflecting the indicator values calculated for the candidates forming the candidate group is calculated. Then, an image within a predetermined area in the inputted image containing the candidate group having the integrated indicator value not less than a second threshold is extracted as the face image.
摘要:
A face discrimnating process judges whether a discrimination target image is an image of a face, based on characteristic amounts of the discrimination target image. A first and a second brightness gradation converting process are administered as preliminary processes. The first brightness gradation converting process is administered on regions in which the degrees of variance of pixel values are greater than or equal to a first predetermined level. The second brightness gradation converting process is administered on regions in which the degrees of variance are less than the first predetermined level. The first brightness gradation converting process causes the degree of variance to approach a second predetermined level. The second brightness gradation converting process suppresses the degree of variance to be less than the second predetermined level.
摘要:
A face discriminating process judges whether a discrimination target image is an image of a face, based on characteristic amounts of the discrimination target image. Gradation conversion of pixel values is administered as a preliminary process, to suppress fluctuations in contrast within the discrimination target image. In the gradation conversion process, degrees of variance of pixel values within local regions of the discrimination target image are caused to approach a predetermined level. The local regions are set to be of a size that includes a single eye of a face to be discriminated.
摘要:
To detect a face image in an inputted image, predetermined-size partial images are cut out at different positions in the inputted image. An indicator value indicating a probability of each partial image being the face image is calculated. The partial images having the indicator values not less than a first threshold are extracted as candidate face images. Each candidate is set as a candidate of interest. If any nearby candidate is present within a predetermined coordinate distance from the candidate of interest, the candidate of interest and the nearby candidate are set in one candidate group. For each candidate group, an integrated indicator value reflecting the indicator values calculated for the candidates forming the candidate group is calculated. Then, an image within a predetermined area in the inputted image containing the candidate group having the integrated indicator value not less than a second threshold is extracted as the face image.